Literature DB >> 32917665

Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk.

Rulla M Tamimi1,2,3, Yujing J Heng4, Kevin H Kensler5, Emily Z F Liu6, Suzanne C Wetstein7, Allison M Onken6, Christina I Luffman6, Gabrielle M Baker6, Laura C Collins6, Stuart J Schnitt8, Vanessa C Bret-Mounet6, Mitko Veta7, Josien P W Pluim7, Ying Liu9, Graham A Colditz9, A Heather Eliassen1,2, Susan E Hankinson1,10.   

Abstract

BACKGROUND: Manual qualitative and quantitative measures of terminal duct lobular unit (TDLU) involution were previously reported to be inversely associated with breast cancer risk. We developed and applied a deep learning method to yield quantitative measures of TDLU involution in normal breast tissue. We assessed the associations of these automated measures with breast cancer risk factors and risk.
METHODS: We obtained eight quantitative measures from whole slide images from a benign breast disease (BBD) nested case-control study within the Nurses' Health Studies (287 breast cancer cases and 1,083 controls). Qualitative assessments of TDLU involution were available for 177 cases and 857 controls. The associations between risk factors and quantitative measures among controls were assessed using analysis of covariance adjusting for age. The relationship between each measure and risk was evaluated using unconditional logistic regression, adjusting for the matching factors, BBD subtypes, parity, and menopausal status. Qualitative measures and breast cancer risk were evaluated accounting for matching factors and BBD subtypes.
RESULTS: Menopausal status and parity were significantly associated with all eight measures; select TDLU measures were associated with BBD histologic subtype, body mass index, and birth index (P < 0.05). No measure was correlated with body size at ages 5-10 years, age at menarche, age at first birth, or breastfeeding history (P > 0.05). Neither quantitative nor qualitative measures were associated with breast cancer risk.
CONCLUSIONS: Among Nurses' Health Studies women diagnosed with BBD, TDLU involution is not a biomarker of subsequent breast cancer. IMPACT: TDLU involution may not impact breast cancer risk as previously thought. ©2020 American Association for Cancer Research.

Entities:  

Mesh:

Year:  2020        PMID: 32917665      PMCID: PMC7642012          DOI: 10.1158/1055-9965.EPI-20-0723

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  29 in total

Review 1.  Development of the human breast.

Authors:  Jose Russo; Irma H Russo
Journal:  Maturitas       Date:  2004-09-24       Impact factor: 4.342

2.  Quantitative Analysis of TDLUs using Adaptive Morphological Shape Techniques.

Authors:  Adrian Rosebrock; Jesus J Caban; Jonine Figueroa; Gretchen Gierach; Laura Linville; Stephen Hewitt; Mark Sherman
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2013-03-29

3.  Age-related lobular involution and risk of breast cancer.

Authors:  Tia R Milanese; Lynn C Hartmann; Thomas A Sellers; Marlene H Frost; Robert A Vierkant; Shaun D Maloney; V Shane Pankratz; Amy C Degnim; Celine M Vachon; Carol A Reynolds; Romayne A Thompson; L Joseph Melton; Ellen L Goode; Daniel W Visscher
Journal:  J Natl Cancer Inst       Date:  2006-11-15       Impact factor: 13.506

4.  Magnitude and laterality of breast cancer risk according to histologic type of atypical hyperplasia: results from the Nurses' Health Study.

Authors:  Laura C Collins; Heather J Baer; Rulla M Tamimi; James L Connolly; Graham A Colditz; Stuart J Schnitt
Journal:  Cancer       Date:  2007-01-15       Impact factor: 6.860

Review 5.  Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies.

Authors:  Andrew G Renehan; Margaret Tyson; Matthias Egger; Richard F Heller; Marcel Zwahlen
Journal:  Lancet       Date:  2008-02-16       Impact factor: 79.321

6.  Radial scars and subsequent breast cancer risk: results from the Nurses' Health Studies.

Authors:  Sarah A Aroner; Laura C Collins; James L Connolly; Graham A Colditz; Stuart J Schnitt; Bernard A Rosner; Susan E Hankinson; Rulla M Tamimi
Journal:  Breast Cancer Res Treat       Date:  2013-04-23       Impact factor: 4.872

7.  Benign breast disease, recent alcohol consumption, and risk of breast cancer: a nested case-control study.

Authors:  Rulla M Tamimi; Celia Byrne; Heather J Baer; Bernie Rosner; Stuart J Schnitt; James L Connolly; Graham A Colditz
Journal:  Breast Cancer Res       Date:  2005-05-16       Impact factor: 6.466

8.  Age-related terminal duct lobular unit involution in benign tissues from Chinese breast cancer patients with luminal and triple-negative tumors.

Authors:  Changyuan Guo; Hyuna Sung; Shan Zheng; Jennifer Guida; Erni Li; Jing Li; Nan Hu; Joseph Deng; Jonine D Figueroa; Mark E Sherman; Gretchen L Gierach; Ning Lu; Xiaohong R Yang
Journal:  Breast Cancer Res       Date:  2017-05-25       Impact factor: 6.466

9.  Association of Body Mass Index and Age With Subsequent Breast Cancer Risk in Premenopausal Women.

Authors:  Minouk J Schoemaker; Hazel B Nichols; Lauren B Wright; Mark N Brook; Michael E Jones; Katie M O'Brien; Hans-Olov Adami; Laura Baglietto; Leslie Bernstein; Kimberly A Bertrand; Marie-Christine Boutron-Ruault; Tonje Braaten; Yu Chen; Avonne E Connor; Miren Dorronsoro; Laure Dossus; A Heather Eliassen; Graham G Giles; Susan E Hankinson; Rudolf Kaaks; Timothy J Key; Victoria A Kirsh; Cari M Kitahara; Woon-Puay Koh; Susanna C Larsson; Martha S Linet; Huiyan Ma; Giovanna Masala; Melissa A Merritt; Roger L Milne; Kim Overvad; Kotaro Ozasa; Julie R Palmer; Petra H Peeters; Elio Riboli; Thomas E Rohan; Atsuko Sadakane; Malin Sund; Rulla M Tamimi; Antonia Trichopoulou; Giske Ursin; Lars Vatten; Kala Visvanathan; Elisabete Weiderpass; Walter C Willett; Alicja Wolk; Jian-Min Yuan; Anne Zeleniuch-Jacquotte; Dale P Sandler; Anthony J Swerdlow
Journal:  JAMA Oncol       Date:  2018-11-08       Impact factor: 31.777

10.  Deep learning assessment of breast terminal duct lobular unit involution: Towards automated prediction of breast cancer risk.

Authors:  Suzanne C Wetstein; Allison M Onken; Christina Luffman; Gabrielle M Baker; Michael E Pyle; Kevin H Kensler; Ying Liu; Bart Bakker; Ruud Vlutters; Marinus B van Leeuwen; Laura C Collins; Stuart J Schnitt; Josien P W Pluim; Rulla M Tamimi; Yujing J Heng; Mitko Veta
Journal:  PLoS One       Date:  2020-04-15       Impact factor: 3.240

View more
  8 in total

1.  Serum hormone levels and normal breast histology among premenopausal women.

Authors:  Mark E Sherman; Thomas de Bel; Michael G Heckman; Launia J White; Joshua Ogony; Melody Stallings-Mann; Tracy Hilton; Amy C Degnim; Robert A Vierkant; Tanya Hoskin; Matthew R Jensen; Laura Pacheco-Spann; Jill E Henry; Anna Maria Storniolo; Jodi M Carter; Stacey J Winham; Derek C Radisky; Jeroen van der Laak
Journal:  Breast Cancer Res Treat       Date:  2022-05-03       Impact factor: 4.624

2.  TDLU Involution and Breast Cancer Risk-Reply.

Authors:  Yujing J Heng; Kevin H Kensler; Gabrielle M Baker; Laura C Collins; Stuart J Schnitt; Rulla M Tamimi
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2021-04       Impact factor: 4.090

3.  Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk-Letter.

Authors:  Amy C Degnim; Derek C Radisky; Celine M Vachon; Mark E Sherman
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2021-04       Impact factor: 4.090

4.  Deep Learning Image Analysis of Benign Breast Disease to Identify Subsequent Risk of Breast Cancer.

Authors:  Adithya D Vellal; Korsuk Sirinukunwattan; Kevin H Kensler; Gabrielle M Baker; Andreea L Stancu; Michael E Pyle; Laura C Collins; Stuart J Schnitt; James L Connolly; Mitko Veta; A Heather Eliassen; Rulla M Tamimi; Yujing J Heng
Journal:  JNCI Cancer Spectr       Date:  2021-01-11

5.  Deep learning-based grading of ductal carcinoma in situ in breast histopathology images.

Authors:  Suzanne C Wetstein; Nikolas Stathonikos; Josien P W Pluim; Yujing J Heng; Natalie D Ter Hoeve; Celien P H Vreuls; Paul J van Diest; Mitko Veta
Journal:  Lab Invest       Date:  2021-02-19       Impact factor: 5.662

6.  Deep learning-based breast cancer grading and survival analysis on whole-slide histopathology images.

Authors:  Suzanne C Wetstein; Vincent M T de Jong; Nikolas Stathonikos; Mark Opdam; Gwen M H E Dackus; Josien P W Pluim; Paul J van Diest; Mitko Veta
Journal:  Sci Rep       Date:  2022-09-06       Impact factor: 4.996

7.  Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning.

Authors:  Mark E Sherman; Jeroen A W M van der Laak; Thomas de Bel; Geert Litjens; Joshua Ogony; Melody Stallings-Mann; Jodi M Carter; Tracy Hilton; Derek C Radisky; Robert A Vierkant; Brendan Broderick; Tanya L Hoskin; Stacey J Winham; Marlene H Frost; Daniel W Visscher; Teresa Allers; Amy C Degnim
Journal:  NPJ Breast Cancer       Date:  2022-01-19

8.  Associations of reproductive breast cancer risk factors with breast tissue composition.

Authors:  Lusine Yaghjyan; Rebecca J Austin-Datta; Hannah Oh; Yujing J Heng; Adithya D Vellal; Korsuk Sirinukunwattana; Gabrielle M Baker; Laura C Collins; Divya Murthy; Bernard Rosner; Rulla M Tamimi
Journal:  Breast Cancer Res       Date:  2021-07-05       Impact factor: 6.466

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.